On male-female pay gap Researchers decompose the pay gap into the portion explained by differences in productivity characteristics and the portion unexplained (discrimination). 2/3 of the pay gap can be explained by differences in experience, industry, occupation, etc. 1/3 is unexplained This is one example of study, other studies have different results Pay gap has been falling equally due to a rise in relative productivity characteristics of women and a decline in the unexplained gap. On black-white pay gap 89% of pay gap can be explained by differences in productivity characteristics.  difference in education diminished and shrunk the gap. payoff to education has risen which expanded the gap.  Evidence
Part of the gender wage gap is the result of rational choices made by women? To work fewer/flexible hours To choose safer less effort-intensive occupations Occupational segregation may be due to women choosing occupations, such as nursing and teaching, with skills that are useful in home production. To take time off for childcare Due to shorter work careers, it is rational for women to invest less in education and training. Their stock of human capital will deteriorate when they are out of the labor force. Do women invest less in human capital  because  of discrimination? Women stay out of the labor force because of the low pay in the labor market. If discrimination declined, then more women may decide to remain single or childless. Rational Choice or Discrimination?
 
Occupational Segregation Definition:  crowding of men into “men’s jobs” and women into “women’s jobs” Duncan Index : a summary measure for an economy used to measure the degree of occupational segregation. S = ½ *   i  M i  - F i  M i , F i  are % males/females in LF who work in occupation i. If no occup segregation, M i  = F i  and so the difference = 0 so S=0. If much segregation, M i  – F i  is a big number and so S is large. With complete segregation, S = 100. S = % M or W who would have to change occupation to eliminate segregation.
two people with same work characteristics Productivity, preferences but different group (race, sex, age) receive different outcomes in labor market  wages, hiring, promotion Wage discrimination  Less pay for doing the same work Occupational job discrimination  restricted from entering some occupations Human capital discrimination  less access to productivity-increasing opportunities such as formal schooling or on-the-job training Employment discrimination  not hired, unemployed Wage Differentials: Discrimination
employers base decisions upon the average characteristics of the group to which they belong Age, education, race, gender and experience provide some information about productivity   imperfect predictors of productivity Gender may provide information on job commitment - women  on average  have higher turnover rates. Race may provide some information about schooling quality - blacks  on average  go to inferior schools than whites. Young males pay higher insurance rates since they have more accidents on average Asians have good IT skills Employers are not malicious in practicing this type of discrimination They gain since they minimize hiring costs Harmed: Workers different from average  Statistical discrimination will diminish if average characteristics of the groups converge over time Statistical Discrimination
Assume men and women are equally productive Prejudiced employer: hires men, pays women less Result of discrimination: women earn less than they would earn in absence of discrimination. Non-discriminatory employers randomly hire men and women, paying the same wage Firms hiring women have lower labor costs then firms hiring just men so firms with women have higher profits non discriminating employers drive discriminating employers out of business Competition should eliminate discrimination So why doesn’t discrimination disappear?  Not enough non-discriminating firms Imperfect competition – no free firm entry Imperfect information about prospective workers Becker’s Theory of Discrimination
Equal Pay Act of 1963   requires that men and women doing the same job to be paid the same. Firms could avoid the law’s requirements conducting employment discrimination (e.g., not hiring females for jobs held by males) . Civil Rights Act of 1964  outlaws both wage discrimination  and   employment discrimination. Applies to race, gender, color, religion, and national origin. Applies to private employers, labor unions, and governments. Firms with more than $50,000 of government contracts must develop  affirmative-action programs .  Firms must a develop plan to hire more women and minorities if the firm has a smaller of proportion of women and minorities than in the available labor force. These programs have been under legal and political attack. Antidiscrimination Policies
To study the earnings gap: Regression analysis fit a linear relationship Y = a + bX + u X, independent variable: education, age, gender, race, expreince Y, dependent variable: earnings how does a change in X cause Y to change? Y = a + bX + u get data on Y, X multiple observations use regression analysis to estimate a and b

Family6 Discr

  • 1.
  • 2.
    On male-female paygap Researchers decompose the pay gap into the portion explained by differences in productivity characteristics and the portion unexplained (discrimination). 2/3 of the pay gap can be explained by differences in experience, industry, occupation, etc. 1/3 is unexplained This is one example of study, other studies have different results Pay gap has been falling equally due to a rise in relative productivity characteristics of women and a decline in the unexplained gap. On black-white pay gap 89% of pay gap can be explained by differences in productivity characteristics. difference in education diminished and shrunk the gap. payoff to education has risen which expanded the gap. Evidence
  • 3.
    Part of thegender wage gap is the result of rational choices made by women? To work fewer/flexible hours To choose safer less effort-intensive occupations Occupational segregation may be due to women choosing occupations, such as nursing and teaching, with skills that are useful in home production. To take time off for childcare Due to shorter work careers, it is rational for women to invest less in education and training. Their stock of human capital will deteriorate when they are out of the labor force. Do women invest less in human capital because of discrimination? Women stay out of the labor force because of the low pay in the labor market. If discrimination declined, then more women may decide to remain single or childless. Rational Choice or Discrimination?
  • 4.
  • 5.
    Occupational Segregation Definition: crowding of men into “men’s jobs” and women into “women’s jobs” Duncan Index : a summary measure for an economy used to measure the degree of occupational segregation. S = ½ *  i  M i - F i  M i , F i are % males/females in LF who work in occupation i. If no occup segregation, M i = F i and so the difference = 0 so S=0. If much segregation, M i – F i is a big number and so S is large. With complete segregation, S = 100. S = % M or W who would have to change occupation to eliminate segregation.
  • 6.
    two people withsame work characteristics Productivity, preferences but different group (race, sex, age) receive different outcomes in labor market wages, hiring, promotion Wage discrimination Less pay for doing the same work Occupational job discrimination restricted from entering some occupations Human capital discrimination less access to productivity-increasing opportunities such as formal schooling or on-the-job training Employment discrimination not hired, unemployed Wage Differentials: Discrimination
  • 7.
    employers base decisionsupon the average characteristics of the group to which they belong Age, education, race, gender and experience provide some information about productivity imperfect predictors of productivity Gender may provide information on job commitment - women on average have higher turnover rates. Race may provide some information about schooling quality - blacks on average go to inferior schools than whites. Young males pay higher insurance rates since they have more accidents on average Asians have good IT skills Employers are not malicious in practicing this type of discrimination They gain since they minimize hiring costs Harmed: Workers different from average Statistical discrimination will diminish if average characteristics of the groups converge over time Statistical Discrimination
  • 8.
    Assume men andwomen are equally productive Prejudiced employer: hires men, pays women less Result of discrimination: women earn less than they would earn in absence of discrimination. Non-discriminatory employers randomly hire men and women, paying the same wage Firms hiring women have lower labor costs then firms hiring just men so firms with women have higher profits non discriminating employers drive discriminating employers out of business Competition should eliminate discrimination So why doesn’t discrimination disappear? Not enough non-discriminating firms Imperfect competition – no free firm entry Imperfect information about prospective workers Becker’s Theory of Discrimination
  • 9.
    Equal Pay Actof 1963 requires that men and women doing the same job to be paid the same. Firms could avoid the law’s requirements conducting employment discrimination (e.g., not hiring females for jobs held by males) . Civil Rights Act of 1964 outlaws both wage discrimination and employment discrimination. Applies to race, gender, color, religion, and national origin. Applies to private employers, labor unions, and governments. Firms with more than $50,000 of government contracts must develop affirmative-action programs . Firms must a develop plan to hire more women and minorities if the firm has a smaller of proportion of women and minorities than in the available labor force. These programs have been under legal and political attack. Antidiscrimination Policies
  • 10.
    To study theearnings gap: Regression analysis fit a linear relationship Y = a + bX + u X, independent variable: education, age, gender, race, expreince Y, dependent variable: earnings how does a change in X cause Y to change? Y = a + bX + u get data on Y, X multiple observations use regression analysis to estimate a and b

Editor's Notes